数据中心
计算机冷却
能量(信号处理)
人工智能
人工神经网络
计算机科学
中心(范畴论)
高效能源利用
机械工程
工程类
物理
电气工程
操作系统
化学
电子设备和系统的热管理
量子力学
结晶学
作者
Bharath Ramakrishnan,Cathy Turner,Husam A. Alissa,Dennis Trieu,Felipe Vega Rivera,L. Joseph Melton,M.V.C. Rao,Sruti Chigullapalli,Tatek Getachew,Vladimir Prodanovic,Robert Lankston,Christian Belady,Vaidehi Oruganti
摘要
Abstract Traditionally, Data Centers (DC) have used air cooling for IT equipment, but as Graphics Processing Units (GPUs) evolve, they demand more power and sophisticated cooling. Aiming for efficiency, Direct Liquid Cooling (DLC) emerges as a promising solution. We evaluated the effectiveness of DLC versus traditional air cooling on a Microsoft G50 GPU server performing AI/ML tasks. The results indicated that DLC greatly enhances GPU performance, increases efficiency by 2.7% in Gflops/s, cuts power usage by 12%, reduces execution times by up to 6.22%, and lowers chip temperatures by 20° compared to air cooling. Our research develops an overall performance metric that considers data center, hardware, and chip levels, concluding that DLC is extremely beneficial for AI workloads, increasing energy savings and balancing performance with power requirements.
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